Evidence map›Paper›PMID 36655786›Full record

ArticleBioinformatics (Oxford, England)2023

DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model.

Stefan Badelt, Ronny Lorenz, Ivo L Hofacker

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Computational modeling of cotranscriptional RNA folding.Computational and structural biotechnology journal · 2025
    Review
  5. Article
  6. Article
  7. DrForna: visualization of cotranscriptional folding.Bioinformatics (Oxford, England) · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Stefan BadeltDepartment of Theoretical Chemistry, University of Vienna, Vienna, Austria.ORCID 0000-0003-2636-5801
Ronny LorenzDepartment of Theoretical Chemistry, University of Vienna, Vienna, Austria.ORCID 0000-0002-2144-698X
Ivo L HofackerDepartment of Theoretical Chemistry, University of Vienna, Vienna, Austria.ORCID 0000-0001-7132-0800
University of Vienna · ATCalifornia Institute of Technology · US

Funding

Austrian Science Foundation
6 · The paper itself

Abstract

motivationFolding during transcription can have an important influence on the structure and function of RNA molecules, as regions closer to the 5' end can fold into metastable structures before potentially stronger interactions with the 3' end become available. Thermodynamic RNA folding models are not suitable to predict structures that result from cotranscriptional folding, as they can only calculate properties of the equilibrium distribution. Other software packages that simulate the kinetic process of RNA folding during transcription exist, but they are mostly applicable for short sequences.

resultsWe present a new algorithm that tracks changes to the RNA secondary structure ensemble during transcription. At every transcription step, new representative local minima are identified, a neighborhood relation is defined and transition rates are estimated for kinetic simulations. After every simulation, a part of the ensemble is removed and the remainder is used to search for new representative structures. The presented algorithm is deterministic (up to numeric instabilities of simulations), fast (in comparison with existing methods), and it is capable of folding RNAs much longer than 200 nucleotides. AVAILABILITY AND IMPLEMENTATION: This software is open-source and available at https://github.com/ViennaRNA/drtransformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

HeuristicsRNA FoldingAlgorithmsNucleic Acid ConformationRNASoftwareRNA

Identifiers

PMID36655786
PMCPMC9889959
OpenAlexW4317433806

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.